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Explainable AI Interpretation of Feature Importance in Growth Prediction

Ai Biofabrication

Deep Learning for Tumor Spheroid Growth Prediction

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Ai Biofabrication › Deep Learning for Tumor Spheroid Growth Prediction

Explainable AI Interpretation of Feature Importance in Growth Prediction

This investigation applies SHAP, LIME, and saliency mapping techniques to interpret which cellular and environmental features most strongly influence spheroid growth predictions from deep learning models. The academic contribution establishes biological interpretability of black-box models and validates that learned decision pathways align with known tumor biology principles.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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